Search results1 – 4 of 4
New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual…
New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.
The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors…
The purpose of this paper is to apply an empirically based approach to develop a decision-making model that comprehensively incorporates the potential affecting factors and the related significant drivers that support network designers in selecting the appropriate strategic supply chain configuration or checking the coherence of an existing supply chain structure in four industry sectors.
The decision-making model is developed based on an empirical study that integrates multiple case studies and statistical analyses. In total, 113 best-in-class manufacturing firms in four sectors are studied to investigate their strategic supply chain configurations and the information of identified affecting drivers. The factor analysis and regression analysis are conducted to classify the drivers into five factor groups, and to identify the significant drivers used to develop the decision-making model.
The findings of this research are three-pronged. First, 12 significant drivers related to 5 factor groups affecting strategic supply chain network design (SCND) are identified. Second, a decision-making model is developed to support users in strategic SCND. Last, the main characteristics of various strategic supply chain configurations are summarized in four industry sectors.
The authors identified valuable insights for both academics and practitioners based on the identified significant affecting drivers and the developed decision-making model. In addition, this study also proposes two potential research lines on the study of additional contextual affecting factors and decision issues in strategic SCND.
This study could be the first attempt to use an empirically based method to develop a decision-making model aimed at supporting the preliminary design of a supply chain network. Therefore, the drawbacks of a pure qualitative conceptual model and optimization model are eliminated.